Dialogue processing systems are expected to come into increasingly widespread use in a variety of speech processing applications, including computer interfaces, automated call handlers, ticket machines, automatic teller machines (ATMs), reservation systems, interactive on-line services, and any other application involving human-machine interaction which can be characterized as a dialogue. If such systems are to become more effective information-seeking, task-executing, and problem-solving agents, they must be able to communicate as effectively with humans as humans do with each other. Conventional dialogue processing systems may be generally classified as question-answer systems, spoken input systems, or variable initiative systems.
In a question-answer system, a user seeks a particular piece of information that the system possesses. Exemplary question-answer systems are described in S. Carberry, "Plan Recognition in Natural Language Dialogue," IT Press, 1990; R. E. Frederking, "Integrated Natural Language Dialogue: a Computational Model," Kluwer Academic Publishers, 1988; G. G. Hendrix, E. D. Sacerdoti, D. Sagalowicz, and J. Slocum, "Developing a Natural Language Interface to Complex Data," ACM Transactions on Database Systems, pp. 105-147, June 1978; R. Wilensky, "The Berkeley UNIX Consultant Project," Computational Linguistics, 14:35-84, 1988; and B. J. Grosz, D. E. Appelt, P. A. Martin, and F. C. N. Pereira, "TEAM: An Experiment in the Design of Transportable Natural Language Interfaces," Artificial Intelligence, 32:173-243, 1987. These question-answer systems generally require user input to be entered via a keyboard, and do not include any significant capability for processing natural spoken language.
Spoken input systems have the added difficulty of requiring robust natural language understanding capabilities. One such system is the MINDS system, described in S. R. Young, A. G. Hauptmann, W. H. Ward, E. T. Smith, and P. Werner, "High Level Knowledge Sources in Usable Speech Recognition Systems," Communications of ACM, pages 183-194, February 1989, which is incorporated by reference herein. The MINDS system uses discourse and dialogue knowledge to aid in the speech recognition task. Another spoken input system is the TINA system, described in S. Seneff, "TINA: A Natural Language System for Spoken Language Applications," Computational Linguistics, pp. 61-86, 1992, which is incorporated by reference herein. This system uses probabilistic networks to parse token sequences provided by a speech recognition system. The VODIS system, described in S. J. Young and C. E. Proctor, "The Design and Implementation Dialogue Control in Voice Operated Database Inquiry Systems," Speech and Language, 329-353, 1989, which is incorporated by reference herein, is a voice operated database inquiry system for a train timetable application. This system uses an object-oriented integrated framework for dealing with interface design, determining how dialogue can aid the recognition process, and providing the dialogue control needed for generating natural speech output. Another spoken input system designed for use in a train timetable application can be found in H. Aust et al., "Philips Automatic Train Timetable Information System," Speech Communication, pp. 249-262, 1995, which is incorporated by reference herein. This system attempts to provide a user-friendly interface, such that users can talk to the system in an unconstrained and natural manner to extract train information. Unfortunately, each of these spoken input systems is generally application specific, and fails to provide a sufficiently general framework for implementing dialogue management across a variety of different applications.
A variable initiative system is one which is capable of taking the initiative in a dialogue under appropriate circumstances, while also knowing when to relinquish the initiative if it determines that the user's input will help guide the system to a quicker solution. An example of such a system is described in D. G. Bobrow, "GUS: A Frame Driven Dialog System," Artificial Intelligence, 155-173, 1977, which is incorporated by reference herein. Conventional variable initiative systems, like the above-noted spoken input systems, are also unable to provide a general dialogue management framework for supporting a large number of diverse applications.
It is therefore apparent that a need exists for dialogue management techniques which are sufficiently general to be used as an application-independent framework for providing dialogue management in a variety of diverse applications.